1 citations · 4 across the 18 of their papers we have counts for
20 papers
DeLo: Dual Decomposed Low-Rank Experts Collaboration for Continual Missing Modality Learning
Xiwei Liu, Yulong Li, Feilong Tang +1
Adapting Large Multimodal Models (LMMs) to real-world scenarios poses the dual challenges of learning from sequential data streams while handling frequent modality incompleteness,…
Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
Huifa Li, Feilong Tang, Haochen Xue +5
Aging is a highly complex and heterogeneous process that progresses at different rates across individuals, making biological age (BA) a more accurate indicator of physiological dec…
SAM-DCE: Decoupled Context Enhancement for Prompt-Free Medical Image Segmentation
Yingzhen Hu, Yiheng Zhong, Ruobing Li +8
The Segment Anything Model (SAM) is a promising foundation model for medical image segmentation, but its prompt-driven design is not directly suitable for fully automatic multi-cla…
DeepGB-TB: A Risk-Balanced Cross-Attention Gradient-Boosted Convolutional Network for Rapid, Interpretable Tuberculosis Screening
Zhixiang Lu, Yulong Li, Feilong Tang +5
Large-scale tuberculosis (TB) screening is limited by the high cost and operational complexity of traditional diagnostics, creating a need for artificial-intelligence solutions. We…
StreamAgent: Towards Anticipatory Agents for Streaming Video Understanding
Haolin Yang, Feilong Tang, Lingxiao Zhao +10
Real-time streaming video understanding in domains such as autonomous driving and intelligent surveillance poses challenges beyond conventional offline video processing, requiring…
Towards Efficient Medical Reasoning with Minimal Fine-Tuning Data
Xinlin Zhuang, Feilong Tang, Haolin Yang +9
Supervised Fine-Tuning (SFT) of the language backbone plays a pivotal role in adapting Vision-Language Models (VLMs) to specialized domains such as medical reasoning. However, exis…
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models
Qiyan Zhao, Xiaofeng Zhang, Yiheng Li +7
Hallucinations pose a significant challenge in Large Vision Language Models (LVLMs), with misalignment between multimodal features identified as a key contributing factor. This pap…
Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
Ankan Deria, Adinath Madhavrao Dukre, Feilong Tang +5
Despite significant advances in inference-time search for vision-language models (VLMs), existing approaches remain both computationally expensive and prone to unpenalized, low-con…
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
Feilong Tang, Chengzhi Liu, Zhongxing Xu +9
Recent advancements in multimodal large language models (MLLMs) have significantly improved performance in visual question answering. However, they often suffer from hallucinations…
Confidence-Aware Self-Distillation for Multimodal Sentiment Analysis with Incomplete Modalities
Yanxi Luo, Shijin Wang, Zhongxing Xu +3
Multimodal sentiment analysis (MSA) aims to understand human sentiment through multimodal data. In real-world scenarios, practical factors often lead to uncertain modality missingn…
SAM-aware Test-time Adaptation for Universal Medical Image Segmentation
Jianghao Wu, Yicheng Wu, Yutong Xie +7
Leveraging the Segment Anything Model (SAM) for medical image segmentation remains challenging due to its limited adaptability across diverse medical domains. Although fine-tuned v…
Towards Dynamic 3D Reconstruction of Hand-Instrument Interaction in Ophthalmic Surgery
Ming Hu, Zhengdi Yu, Feilong Tang +7
Accurate 3D reconstruction of hands and instruments is critical for vision-based analysis of ophthalmic microsurgery, yet progress has been hampered by the lack of realistic, large…
DeepChest: Dynamic Gradient-Free Task Weighting for Effective Multi-Task Learning in Chest X-ray Classification
Youssef Mohamed, Noran Mohamed, Khaled Abouhashad +5
While Multi-Task Learning (MTL) offers inherent advantages in complex domains such as medical imaging by enabling shared representation learning, effectively balancing task contrib…
TAGS: A Test-Time Generalist-Specialist Framework with Retrieval-Augmented Reasoning and Verification
Jianghao Wu, Feilong Tang, Yulong Li +5
Recent advances such as Chain-of-Thought prompting have significantly improved large language models (LLMs) in zero-shot medical reasoning. However, prompting-based methods often r…
Rhythm of Opinion: A Hawkes-Graph Framework for Dynamic Propagation Analysis
Yulong Li, Zhixiang Lu, Feilong Tang +8
The rapid development of social media has significantly reshaped the dynamics of public opinion, resulting in complex interactions that traditional models fail to effectively captu…
PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation
Yiheng Zhong, Zihong Luo, Chengzhi Liu +7
Segment Anything Model (SAM) demonstrates powerful zero-shot capabilities; however, its accuracy and robustness significantly decrease when applied to medical image segmentation. E…
Enforcing Consistency and Fairness in Multi-level Hierarchical Classification with a Mask-based Output Layer
Shijing Chen, Shoaib Jameel, Mohamed Reda Bouadjenek +6
Traditional Multi-level Hierarchical Classification (MLHC) classifiers often rely on backbone models with independent output layers. This structure tends to overlook the hierar…
MSWAL: 3D Multi-class Segmentation of Whole Abdominal Lesions Dataset
Zhaodong Wu, Qiaochu Zhao, Ming Hu +13
With the significantly increasing incidence and prevalence of abdominal diseases, there is a need to embrace greater use of new innovations and technology for the diagnosis and tre…
MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation
Haochen Xue, Feilong Tang, Ming Hu +13
Recent multimodal large language models (MLLMs) have demonstrated significant potential in open-ended conversation, generating more accurate and personalized responses. However, th…
Decoding the Flow: CauseMotion for Emotional Causality Analysis in Long-form Conversations
Yuxuan Zhang, Yulong Li, Zichen Yu +5
Long-sequence causal reasoning seeks to uncover causal relationships within extended time series data but is hindered by complex dependencies and the challenges of validating causa…